Auth Bypass in Axum with Dynamodb

An Auth Bypass in an Axum service that uses DynamoDB as the identity store typically occurs when authorization checks are incomplete or when authentication tokens are accepted but not properly validated before data access. Axum, a web framework for Rust, does not enforce authorization by itself; it relies on application logic to validate authentication and scope. If the application retrieves user data directly from DynamoDB using an identifier extracted from an unverified or loosely validated token (for example, a subject claim in a JWT), an attacker who can influence or forge that identifier can access other users’ data.

DynamoDB does not perform application-level authorization; it only provides low-level access based on the credentials used to sign requests. When Axum calls DynamoDB using an SDK client configured with broad permissions (to simplify development), and the application uses an ID from the token directly as a DynamoDB key (e.g., partition key user_id), there is a risk that the application either skips the ownership check or uses an ID supplied by the client. An attacker who manipulates the token or parameter to another user_id can thereby read or modify data belonging to other users, resulting in a Broken Level of Access (BOLA) / IDOR pattern.

In practice, this can happen when routes use path parameters like user_id without confirming that the authenticated subject matches that parameter, or when DynamoDB queries use a filter expression that is improperly constructed or missing. For example, if an endpoint uses a filter that only checks a partition key without verifying that the authenticated subject equals that key, the request may return data across users. Because DynamoDB responses contain only the requested items and do not indicate authorization context, the application must enforce ownership checks explicitly. Without such checks, the API surface remains unauthenticated in practice for that data access path, and a security risk score reflecting BOLA/IDOR findings will be issued by middleBrick.

Additionally, if the Axum application deserializes DynamoDB responses into generic structures and exposes them directly, sensitive attributes such as administrative flags or email addresses may be returned to clients that should not see them. This data exposure increases the severity of findings related to Property Authorization and Data Exposure checks. Proper mitigation requires validating the authenticated identity against the requested resource on every request, using secure token handling, and ensuring that DynamoDB queries encode the subject as part of the key or are tightly scoped with conditional expressions.

To remediate Auth Bypass risks when using Axum with DynamoDB, enforce strict ownership checks and scope the DynamoDB queries to the authenticated subject. Always derive the partition key from the authenticated identity rather than from user-supplied input. Below are concrete, working examples that demonstrate secure patterns.

Secure route with authenticated subject used as DynamoDB key

Use Axum extractors to obtain the authenticated subject and construct DynamoDB keys safely. This ensures that the resource requested matches the authenticated identity.

use axum::{routing::get, Router, extract::State, http::StatusCode};
use aws_sdk_dynamodb::Client;
use serde::Deserialize;

#[derive(Deserialize)]
struct Claims {
    sub: String,
}

struct AppState {
    ddb: Client,
    table_name: String,
}

async fn get_user_profile(
    State(state): State<AppState>,
    user_claims: Claims,
) -> Result<(StatusCode, String), (StatusCode, String)> {
    let key = aws_sdk_dynamodb::model::AttributeValue::S(user_claims.sub.clone());
    let request = state.ddb
        .get_item()
        .table_name(&state.table_name)
        .key("user_id", key)
        .send()
        .await
        .map_err(|_| (StatusCode::INTERNAL_SERVER_ERROR, "DynamoDB error".to_string()))?;

    match request.item() {
        Some(item) => {
            let email = item.get("email")
                .and_then(|v| v.s.as_ref())
                .ok_or((StatusCode::INTERNAL_SERVER_ERROR, "Missing email".to_string()))?;
            Ok((StatusCode::OK, email.to_string()))
        }
        None => Err((StatusCode::NOT_FOUND, "Profile not found".to_string())),
    }
}

fn build_app(ddb: Client, table_name: String) -> Router {
    Router::new()
        .route("/profile", get(get_user_profile))
        .with_state(AppState { ddb, table_name })
}

Query with explicit filter when multiple items share a partition key

If your data model requires multiple items per user, scope queries with a condition that ties the item ownership to the authenticated subject.

async fn list_user_items(
    State(state): State<AppState>,
    user_claims: Claims,
) -> Result<(StatusCode, Vec<String>), (StatusCode, String)> {
    let partition_key = aws_sdk_dynamodb::model::AttributeValue::S(user_claims.sub);
    let request = state.ddb
        .query()
        .table_name(&state.table_name)
        .key_condition_expression("user_id = :uid")
        .expression_attribute_values(
            ":uid",
            aws_sdk_dynamodb::model::AttributeValue::S(partition_key.s().unwrap_or_default().to_string()),
        )
        .filter_expression("attribute_exists(item_id)")
        .send()
        .await
        .map_err(|_| (StatusCode::INTERNAL_SERVER_ERROR, "Query failed".to_string()))?;

    let items = request.items().unwrap_or_default();
    let ids: Vec<String> = items.iter()
        .filter_map(|item| item.get("item_id").and_then(|v| v.s.as_ref()).map(String::from))
        .collect();
    Ok((StatusCode::OK, ids))
}

Remediation guidance summary

• Never trust client-supplied identifiers for authorization; always use the authenticated subject to scope queries.
• Structure DynamoDB keys so that the partition key includes the subject (e.g., USER#1234) and avoid scanning or filtering across all users.
• Apply explicit filter expressions to enforce ownership at the query level, even when the key is scoped correctly.
• Limit the attributes returned by DynamoDB to the minimum required, reducing Data Exposure risks.

By combining these patterns, Axum applications can mitigate Auth Bypass risks associated with DynamoDB and align with checks such as BOLA/IDOR and Property Authorization that middleBrick evaluates during scans.